Links between the development of early literacy and math skills are well documented. This systematic review focuses on how literacy is incorporated into informal math intervention studies for children in preschool to third grade, which has implications for researchers and those training caregivers to support their children at home. We reviewed 51 experimental or quasi-experimental studies published from 1981 to 2021 that investigated the effectiveness of math interventions in informal learning environments with a caregiver interventionist. Findings revealed that 100% of studies included literacy in some way. We also investigated what types of literacy activities were integrated, how literacy was a part of data sources collected, and in what ways literacy was mentioned explicitly by authors in research reports. The most common literacy activity was speaking and listening, and the most frequently included literacy data source was standardized literacy achievement measures. Finally, researchers in the included studies did not detail literacy throughout their research reports. While early math interventions often integrate literacy, the research base including math interventions would benefit from more explicit rationales for their use of literacy, and caregivers should be provided information to help understand how literacy should be a part of the way they work with their child on math at home. Given that 100% of the informal math intervention studies reviewed for children in preschool to third grade included literacy in some capacity, priority should be given to supporting early childhood educators and parents with an integrated approach to learning (i.e., using math and literacy simultaneously in learning opportunities) in informal settings.The most common literacy activity included in early math intervention studies was speaking and listening; thus, early childhood education professionals and parents should frequently and strategically have dialogue with children as they engage in literacy and math interactions and activities. For example, children should have discussions about the definition of relevant vocabulary and should be given opportunities to practice using the vocabulary with support.Over 60% of the informal math intervention studies reviewed required that child participants read. This points to the necessity of early childhood educators and parents purposefully supporting students with reading as they work with children during math activities. In other words, children need to read and discuss regularly, as well as have others read to them, as part of math activities.

The purpose of this systematic review was to identify how the home learning environment (HLE) was measured in group design, early math intervention studies conducted in the home. Specifically, we evaluated the physical (e.g. frequency of activities) and affective (e.g. parents' beliefs, children's attitudes) aspects of the HLE. We included intervention studies conducted with parents and young children (ages 3-9 years old) that also included instruments designed to measure the HLE. We included 16 studies that used 21 HLE instruments (16 surveys, 3 interviews, 2 focus groups); we coded the characteristics of the HLE instruments, including which physical and affective aspects of the HLE the instruments measured. In most cases, parents responded to the instruments; whereas, only two studies used instruments that captured children's perspectives of the HLE. The instruments measured physical aspects more often than affective aspects of the HLE. Findings from this systematic review highlight implications for measuring the HLE and intervention development and implementation.

The characterization of an effect size is best made in reference to effect sizes found in the literature. A random-effects meta-analysis is the systematic synthesis of related effects from across a literature, producing an estimate of the distribution of effects in the population. We propose using the estimated mean and variance from a random-effects meta-analysis to inform the characterization of an observed effect size. The percentile of an observed effect size within the estimated distribution of population effects can describe the magnitude of the observed effect. Because there is uncertainty in the population estimates, we propose using the prediction distribution (used frequently to estimate the prediction interval in a meta-analysis) to serve as the reference distribution when characterizing an effect size. Doing so, the percentile of an observed effect and the limits of the effect size's 95% confidence interval within the prediction distribution are calculated. With numerous meta-analyses available including various outcomes and contexts, the presented method can be useful to many researchers and practitioners. We demonstrate the application of an easy-to-use Excel worksheet to automate these percentile calculations. We follow this with a simulation study evaluating the method's performance over a range of conditions. Recommendations (and cautions) for meta-analysts and researchers conducting a single study are provided.

The purposes of this study included conducting a meta-analysis and reviewing the study reporting quality of math interventions implemented in informal learning environments (e.g., the home) by children’s caregivers. This meta-analysis included 25 preschool to third-grade math interventions with 83 effect sizes that yielded a statistically significant summary effect (g = 0.26, 95% CI [0.07, 0.45) on children’s math achievement. Significant moderators of the treatment effect included the intensity of caregiver training and type of outcome measure. There were larger average effects for interventions with caregiver training that included follow-up support and for outcomes that were comprehensive early numeracy measures. Studies met 58.0% of reporting quality indicators, and analyses revealed that quality of reporting has improved in recent years. The results of this study offer several recommendations for researchers and practitioners, particularly given the growing evidence base of math interventions conducted in informal learning environments. © 2023 AERA.